1375-P: Why Some Patients Tolerate Severe Insulin Resistance Longer—Insights from Familial Partial Lipodystrophy
Bibliographic record
Abstract
Introduction and Objective: Familial partial lipodystrophy (FPLD) is a rare genetic disorder characterized by selective subcutaneous fat loss alongside metabolic changes like severe insulin resistance. Despite this, not all patients with FPLD develop diabetes, suggesting the presence of further risk modifiers. In common type 2 diabetes, beta cell capacity determined through polygenic risk appears to play a crucial role. We investigated whether a family history of diabetes, which can indicate polygenic risk, determines similar risk in FPLD patients. Methods: We analyzed data from FPLD patients with available information on diabetes status and family history of diabetes within the European Consortium of Lipodystrophies (ECLip) registry. We included all forms of FPLD with at least 5 patients present within ECLip (N = 253, diabetes present in N = 171). Results: Lifetime prevalence of diabetes was significantly different between FPLD subtypes (p < 0.0001) but not between patients with/without a family history of diabetes (p = 0.8). However, having a family history of diabetes was significantly associated with an earlier age of diagnosis of diabetes, which was independent of FPLD subtype (average age of diagnosis with/without a family history = 41.5 and 54.9 years, respectively; 13.4 years earlier diabetes onset, adj.p = 0.0164). Conclusion: Having a family history of diabetes is linked to a much earlier age of diabetes onset, independent of the genetic variant causing FPLD. This suggests that common polygenic diabetes risk may impair beta cell compensatory capacity, accelerating diabetes onset in the severe insulin resistant milieu. Even with low polygenic risk, beta cell capacity appears to exhaust with age, explaining the high lifetime prevalence of diabetes in FPLD. Characterizing these polygenic mechanisms could reveal determinants of beta cell compensation, with potential implications for diabetes risk in more common, less severe insulin-resistant states. Disclosure M. Ennis: Other Relationship; Novo Nordisk. K. Ulrich: None. G. Ufer: Other Relationship; Boehringer-Ingelheim, Lilly Diabetes. R. Sabia: None. M. Beghini: None. G. Ceccarini: Speaker's Bureau; Novo Nordisk, Rhythm Pharmaceuticals, Inc. Consultant; Amryt Pharma. Speaker's Bureau; Chiesi. H.D. Dupuis: None. A. Fernandez-Pombo: None. K. Miehle: Research Support; Amryt Pharma. L. Palladino: None. F. Prodam: Consultant; Novartis Pharmaceuticals Corporation. Speaker's Bureau; Novo Nordisk. Consultant; Amryt Pharma. Speaker's Bureau; Amryt Pharma, Menarini. M. Romanisio: None. A. Stears: None. I. Stotl: None. M. Vantyghem: Other Relationship; Elsevier. Research Support; Amryt Pharma, Takeda Pharmaceutical - Canada. Speaker's Bureau; Sanofi. Advisory Panel; Vertex Pharmaceuticals Incorporated. Research Support; Vertex Pharmaceuticals Incorporated. C. Vatier: Consultant; Abbott, Sanofi, Regeneron Pharmaceuticals, Novo Nordisk, Lilly Diabetes, AstraZeneca, Menarini. C. Vigouroux: Other Relationship; Amryt Pharma, Amryt Pharma, Sanofi. E. Withers: None. B. Akinci: Consultant; Regeneron Pharmaceuticals, Amryt Pharma, Alnylam Pharmaceuticals, Inc. D. Araujo-Vilar: Consultant; Amryt Pharma. J. von Schnurbein: Speaker's Bureau; Amryt Pharma. Advisory Panel; Rhythm Pharmaceuticals, Inc. M. Wabitsch: Consultant; Novo Nordisk, Nestlé Health Science, Chiesi Farmaceutici, Rhythm Pharmaceuticals, Inc, Abbott. Other Relationship; Merck Healthcare Germany, Novo Nordisk, Rhythm Pharmaceuticals, Inc, Chiesi Farmaceutici, SYNLAB, Abbott, Sandoz, InfectoPharm, Mediagnost, Ascendis Pharma A/S, Hexal AG, Novo Nordisk, Merck Healthcare Germany, Abbott, Sandoz, SYNLAB. Board Member; Chiesi Pharmaceutici, Rhythm Pharmaceuticals, Inc, Novo Nordisk, Nestlé Health Science, Abbott. M. Heni: Advisory Panel; Amryt Pharma. Speaker's Bureau; Amryt Pharma, AstraZeneca, Boehringer-Ingelheim. Advisory Panel; Boehringer-Ingelheim. Speaker's Bureau; Lilly Diabetes, Novartis AG, Novo Nordisk, Sanofi.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".